Hadoop on Linux: Easy Quick-Start Guide

August 7, 2025 | By the+gnu+linux+evangelist.

Deploy a Single-Node Hadoop Cluster on Linux in Under 10 Minutes

Deploy a Single-Node Hadoop Cluster on Linux fast and easy. Start processing Big Data in minutes with this quick setup.

Install Hadoop, configure HDFS and YARN, and run a MapReduce Job — all under 10 minutes.

This is a beginner-friendly guide to setting up Apache Hadoop on your Linux machine step-by-step.

Perfect for testing Hadoop on Ubuntu, Fedora, Debian, and more — without cluster complexity.

Ensure Java and Hadoop paths are correctly set:

export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64

export HADOOP_HOME=~/hadoop

export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin

3. Start HDFS and YARN Services

To start Hadoop HDFS and YARN on Linux:
```
start-dfs.sh
```
```
start-yarn.sh
```
4. Verify Hadoop Daemons

Check all Hadoop services are running properly:
```
jps
```
You should see:
- NameNode
- DataNode
- ResourceManager
- NodeManager
5. Access Web UIs

Visit the Hadoop Web Interfaces:
- http://localhost:9870 – NameNode UI
- http://localhost:8088 – ResourceManager UI
6. Create Your HDFS User Directory

To create your own HDFS user folder:
```
hdfs dfs -mkdir -p /user/$(whoami)
```
7. Upload a File to HDFS

Create and upload a test file into Hadoop Distributed File System:
```
echo "Hello Hadoop" > sample.txt
```
```
hdfs dfs -put sample.txt /user/$(whoami)/
```
8. List Files in Your HDFS Folder

Check that the file was uploaded correctly:
```
hdfs dfs -ls /user/$(whoami)/
```

Execute the default WordCount example on the input file:

hadoop jar $HADOOP_HOME/share/hadoop/mapreduce/hadoop-mapreduce-examples-*.jar wordcount /user/$(whoami)/sample.txt /user/$(whoami)/output